Webb15 nov. 2024 · Shape must be rank 2 but is rank 1 during model.fit #154. Closed italodamato opened this issue Nov 15, 2024 · 1 comment Closed Shape must be rank 2 … WebbI'm new to tensorflow and I'm trying to update some code for a bidirectional LSTM from an old version of tensorflow to the newest (1.0), but I get this error: Shape must be rank 2 …
Shape must be rank 2 but is rank 1 during model.fit #154 - Github
Webb18 juni 2024 · no actual solution in the answers, different input code - ValueError: Shape must be rank 2 but is rank 3 for 'MatMul' python; python-3.x; tensorflow; keras; lstm; … Webb8 jan. 2024 · 如果超过数组的维度,如下: c = tf.concat([a,b],1) 1 则会报, ValueError: Shape must be at least rank 2 but is rank 1 for 'concat' ,意思是数组至少是二维,axis才能为1。 二维数组 rofi shortcut
ValueError: Shape must be rank 2 but is rank 1 for
Webb24 mars 2024 · Full error message: ValueError: Shape must be rank 2 but is rank 3 for ‘{{node in_top_k/InTopKV2}} = InTopKV2[T=DT_INT64](sequential_1/dense_85/Softmax, … Webb29 nov. 2016 · In your case, x is a matrix of shape (2, 12) and rank 2, so TensorFlow is throwing an error Shape (2, 12) must have rank 1. Obviously the shape (2, 12) will never … Webb18 feb. 2024 · You can use tf.expand_dims(a,0) and tf.expand_dims(b,1) to have rank 2 shapes. Try the following code: a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], name='a') b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], name='b') c = tf.matmul(tf.expand_dims(a,0), … our future health polygenic risk score